This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.4704
Overall Precision: 0.0
Overall Recall: 0.0
Overall F1: 0.0
Overall Accuracy: 0.8065
Email F1: 0.0
Lastname F1: 0.0
Prefix F1: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.2
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Accuracy	Lastname F1	Prefix F1	Username F1
No log	1.0	1	2.5786	0.0	0.0	0.0	0.0
No log	2.0	2	2.3959	0.1774	0.0	0.0	0.0
No log	3.0	3	2.0696	0.8065
No log	4.0	4	1.8231	0.8065
No log	5.0	5	1.6430	0.8065
No log	6.0	6	1.5266	0.8065
No log	7.0	7	1.4704	0.8065

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

burkelive/distilbert-base-uncased-pii-200

distilbert-base-uncased-pii-200

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

burkelive/
distilbert-base-uncased-pii-200